Description: 对“Blocks”信号加上高斯白噪声，再用 db3 小波进行分解,以说明三种取阈值方法和三种噪声标志对去噪性能的影响。-right "Blocks" signal with white Gaussian noise, and then db3 wavelet decomposition, to illustrate three thresholding methods and three noise signs of de-noising performance. Platform: |
Size: 1305 |
Author:黄海滨 |
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Description: 对“Blocks”信号加上高斯白噪声，再用 db3 小波进行分解,以说明三种取阈值方法和三种噪声标志对去噪性能的影响。-right "Blocks" signal with white Gaussian noise, and then db3 wavelet decomposition, to illustrate three thresholding methods and three noise signs of de-noising performance. Platform: |
Size: 1024 |
Author:黄海滨 |
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Description: 两种阈值基于小波变换的阈值方法的比较和介绍，并给出了详细的说明-Two thresholds based on wavelet transform thresholding methods and the introduction and give a detailed description of Platform: |
Size: 194560 |
Author:黎明 |
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Description: 利用emd对一维信号进行去噪的最新程序。包含了三种emd去噪方法：1、直接使用小波阈值，进行硬阈值去噪；2、使用具有emd分解特性的阈值去噪；3、emd分解后的平移不变去噪。-Using emd on one-dimensional signal de-noising of the latest procedures. Emd contains three kinds of de-noising methods: a direct use of wavelet thresholding to carry out hard-threshold de-noising 2, using a emd decomposition characteristics of the threshold de-noising 3, emd decomposition of the translation invariant de-noising. Platform: |
Size: 6144 |
Author:王文波 |
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Description: 小波方法和偏微分方程方法是图像去噪中的主要方法。该文提出基于离散小波变换对图像进行阈值去噪，得出了小波阈值的偏微
分方程表示形式，在此基础上研究偏微分方程的解法，采用分数步的小波阈值方法对图像去噪，得到了较好的去噪效果，同时可以保护边
缘。数值试验结果表明，该方法具有比小波方法更好的去噪效果，能获得较高的信噪比-Wavelet method and partial differential equations is the main method of image denoising. In this paper, based on discrete wavelet transform image threshold denoising, wavelet threshold obtained indicated that the form of partial differential equations, in this study based on the solution of partial differential equations, using fractional steps of wavelet thresholding methods for image to noise, have been well de-noising effect at the same time can protect the edge. Numerical experimental results show that the method is better than the wavelet method for denoising results are able to obtain a higher signal to noise ratio Platform: |
Size: 1305600 |
Author:MaxineChan |
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Description: 对设备进行故障诊断的主要方法就是测量故障
设备的振动或噪声, 并对其进行分析, 从而找出故障原因。然而振动或噪声信号中除了对分析故障有用的信息外, 还有大量的噪声成分。只有有效地滤除噪声, 才能获得有用的信息, 从而得到可靠的分析结论。传统的滤噪方法是将被噪声污染的信号通过一个滤波器, 滤掉噪声频率成分。但对于短时瞬态信号、非平稳信号、含宽带噪声的信号, 采用传统处理方法有着明显的局限性。小波变换为信号去噪提供了一种有效的方法, 小波阈值去噪具有传统方法不可比拟的优越性。但是小波分解的频域重叠性和阈值选取的不确定性, 使得小波阈值去噪法有也不能得到理想效果。-Equipment fault diagnosis method is to measure the fault
Equipment vibration or noise, and its analysis in order to identify the cause of the malfunction. Vibration or noise signals, however, in addition to the analyze fault useful information, there is a lot of noise components. Only effectively filter out the noise in order to obtain useful information, to obtain reliable conclusions. Traditional filtering method based noise pollution signal through a filter to filter out the noise frequency components. But for the short-term transient signal, non-stationary signals, including broadband noise signal, using the traditional approach has obvious limitations. The wavelet transform provides an effective method for signal de-noising, wavelet thresholding has incomparable superiority of traditional methods. Wavelet frequency domain overlap threshold uncertainty, the wavelet thresholding method can not get the desired effect. Platform: |
Size: 267264 |
Author:哈哈 |
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Description: 基于小波变换的随机噪声降噪的matlab 主要运用的方法有软阈值去噪法和硬阈值去噪法-Based on wavelet transform matlab random noise and noise reduction methods are mainly used soft thresholding method and hard thresholding method Platform: |
Size: 72704 |
Author:lisa |
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Description: 小波分解，提取系数，以及各种不同阈值去噪方法，比较全面，可以参考一下-Wavelet decomposition, extraction coefficient, and a variety of different thresholding methods, more comprehensive, you can refer to Platform: |
Size: 1024 |
Author:金豆豆 |
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Description: Gaussian的小波去噪工具箱，基于matlab-Gaussian Wavelet Denoising Matlab Toolbox
Various wavelet shrinkage and wavelet thresholding estimators, appeared in the nonparametric regression literature, are implemented in MATLAB§. These estimators arise from a wide range of classical and empirical Bayes methods treating either individual or blocks of wavelet coefficients. Platform: |
Size: 294912 |
Author:hanyue |
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Description: 小波阈值去噪的各种方法研究，包括软硬阈值函数去噪，新的阈值函数去噪-Wavelet thresholding study various methods, including hard and soft threshold function de-noising, the new threshold function de-noising Platform: |
Size: 78848 |
Author:吴为 |
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Description: ：提出一种基于对偶树复小波块阈值的信号降噪方法，并将其成功应用于机械故障诊断中。机械设备的振动信号都或多或少地含有噪声，导致弱故障信息的提取一直是故障诊断的难点和热点。提出的降噪方法充分利用对偶树复小波变换的平移不变性和块阈值法的更优估计特性，可以获得比常规的小波降噪方法以及基于常规离散正交小波变换的 NeighBlock 降噪法更高的信噪比， 不仅能有效抑制高斯白噪声， 还能够去除冲击信号中的脉冲噪声。-：A denoising method of block thresholding based on
DT-CWT (Dual-tree complex wavelet transform) is proposed,
aiming at the difficulty of extracting weak failure information in
machinery vibration signals. The presented method can obtain
higher signal-to-noise ratio (SNR) than NeighBlock and other
common methods based on orthonormal discrete wavelet trans-
form, because of improving asymptotic optimality of block
thresholding estimator and shift invariance of DT-CWT. It can
not only suppress white Gaussian noise, but also remove spike
pulse noise in impulsive signal effectively. Platform: |
Size: 292864 |
Author:侯蒙蒙 |
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Description: In this paper, a robust DWPT based adaptive bock algorithm with modified threshold for denoising the sounds of musical instruments is proposed. The signal is first segmented into multiple blocks depending upon the minimum mean square criteria in each block, and then thresholding methods are used for each block. All the blocks obtained after denoising the individual block are concatenated to get the final denoised signal. The discrete wavelet packet transform provides more coefficients than the conventional discrete wavelet transform (DWT), representing ad-ditional subtle detail of the signal but decision of optimal decomposition level is very important. Hence, the optimal wavelet and level of decomposition may be different for each signal. The obtained denoised signal with this algorithm is close to the original signal. -In this paper, a robust DWPT based adaptive bock algorithm with modified threshold for denoising the sounds of musical instruments is proposed. The signal is first segmented into multiple blocks depending upon the minimum mean square criteria in each block, and then thresholding methods are used for each block. All the blocks obtained after denoising the individual block are concatenated to get the final denoised signal. The discrete wavelet packet transform provides more coefficients than the conventional discrete wavelet transform (DWT), representing ad-ditional subtle detail of the signal but decision of optimal decomposition level is very important. Hence, the optimal wavelet and level of decomposition may be different for each signal. The obtained denoised signal with this algorithm is close to the original signal. Platform: |
Size: 227328 |
Author:noufan |
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Description: 我按这篇文章做的，广义高斯分布及其在图像去噪中的应用，没有完全做出来，谁做出来了，分享一下- The statistics of imagewavelet coefficients is non2Gaussian and can be described by generalized Gaussian
distribution (GGD). The paper investigates the issues of GGD statisticalmodel for wavelet coefficients in a sub2
band and the corresponding parameters estimation . A Bayesian estimate based subband adaptive thresholding de2
noising algorithm is designed, and the performance of noise reduction of this algorithm, compared with other clas2
sicalwavelet thresholding denoising methods, is discussed according to simulation results .
Keywords image wavelet coefficients generalized Gaussian distribution BayesShrink algorithm image de Platform: |
Size: 342016 |
Author:李胖子 |
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Description: 利用小波进行硬阈值和软阈值去噪，将二者进行比较，并采用峰值信噪比评价图像质量，画出硬阈值和软阈值两种方法的峰值信噪比随噪声方差的变化曲线。-Using wavelet hard threshold and soft thresholding, we will compare the two and uate the image quality using a peak signal to noise ratio, change PSNR draw hard threshold and soft threshold of the two methods with noise variance curve. Platform: |
Size: 152576 |
Author:崔珊珊 |
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Description: 各种方法的去噪程序
den1.m 使用半软阈值方法对图像进行去噪
den1_5_1.m 半软阈值的改进方法 对第一层重构图像进行均值滤波
den1_9.m 半软阈值的改进方法 将线性衰减的函数改为指数的
den1_10.m 半软阈值的改进方法 对第一层的重构图像再次进行小波阈值去噪
den2.m 用软硬阈值函数的改进方法进行去噪
den3.m 用广义阈值函数进行去噪
den4.m 用自适应特征阈值函数进行去噪
wdenoise.m 用Donoho阈值或Birge-Massart策略及软阈值或硬阈值函数进行去噪
meanfilter.m 均值滤波方法进行去噪(对比用)
medfilter.m 中值滤波方法进行去噪(对比用)-Denoising procedures for various methods
Den1.m using semi soft threshold method for image denoising
The improved method of den1_5_1.m semi soft threshold for the first layer of the reconstructed image
The improved method of den1_9.m semi soft threshold will be changed linear to exponential.
The improved method of den1_10.m semi soft threshold for the first layer of the reconstructed image again for wavelet thresholding denoising
Den2.m using the soft and hard threshold function to improve the method of denoising
Den3.m using generalized threshold function for denoising
Den4.m with adaptive feature threshold function for denoising
Wdenoise.m with Donoho threshold or Birge-Massart strategy and soft threshold or hard threshold function for denoising
Meanfilter.m mean filtering method for denoising (contrast)
Medfilter.m median filtering method for denoising (contrast) Platform: |
Size: 641024 |
Author:李松 |
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Description: Edge detection is widely used in image processing, image recognition and computer vision. Tradition edge detection
methods have a lot of disadvantages. This paper presents a new edge detection algorithm base on Matching Pursuit
(MP). Our method has four steps. Firstly, the color image is converted to gray Image. Secondly, the residual part of
Matching Pursuit algorithm with the Wavelet Packet dictionary is extracted. Thirdly, the Gaussian Filter is applied to
remove the additional parts of the previous image and finally, the Ostu’s thresholding method converts image to
binary form. We compared our algorithm with the tradition methods like Prewitt, Sobel, Laplacian of Gaussian (LOG)
and Canny operators. Results show that our algorithm has high value of Performance parameters such as PR, PSNR
and FOM compared to other algorithms. Platform: |
Size: 1069056 |
Author:sacoura |
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Search - wavelet thresholding methods